Suppose a forecaster has 110 predictors ( \(X\) 's) she could use to predict \(Y\) and 150 monthly time series observations. Explain why an OLS regression of \(Y_{t}\) on the first lag of the \(X\) 's is likely to produce poor one-step ahead forecasts. How does the dynamic factor model, estimated using principal components, address this problem?